Forex Dealing Break Down (1)  Click on the link to you to open the “pdf” graphic of trade execution flow exchange comparisons between retail traders and High Frequency Trading algorithmic “machine-to-machine” trade executions.

How Slow is the NBBO?

A Comparison with Direct Exchange Feeds

the oracle machine”

Thirty percent of Wall Street’s intraday liquidity is transformed through price formation acceleration, explicitly influenced by high frequency trading thriving in millions of dollars of profits by exploiting the exchange’s trade execution “latency” electronically sent over the Internet ot capture the “best price” trade executions for the consumer trader.

To be efficiently profitable as a predator on incoming bid/ask trades, the HFT servers are set up is co-located server near an exchange/electronic communications network premise and plugged into a ultra-fast bandwidth. Through network stacking, messaging protocols and raw market data processing.

Though the financial media claims HFT brings greater “liquidity” to the market, in reality it is causing price dislocation for the consumer day trader. For example, the NP-Hard can be used as source code applied to the arbitrage decision problem presented by the variance of the bid and ask spread among the exchanges data flows. Here is where the “investors” and “brokers” can virtually integrate the exchanges through their computational technology without “transparency” to the consumer trader.

clock-rate – faster to market”

Likening the linear exchanges to a convex polyhedral geometric, the functional aspect of the HFT algorithm parameter compilers are encoded into proprietary computational complexity that solves the “problem” through polynomial time within the concrete semantics of an oracle machine or “black box”.

The HFT algorithms must be able to reconfigure frequently in a compute-intensive application to efficiently respond to public data order flows, thus HFT platforms have utilized custom-optimized “field programmable gate array” (FPGA) integrated circuits.

Contemporary (FPGA) optimize I/O speed and allow for programmable logic blocks to be wired together. This is key to minimizing data flow through the bandwidth to the exchange. Though time consuming to program these “logic blocks” can be configured to perform complex combination functions.

Moreover, as mentioned above, soft processor cores implemented with FPGA logic are equally robust. Achieving the ability to be re-programmable at “run time” is leading the FinTech pack with these HFT systems; including non-FPGA architectures (

ref: Redline Trading Sources).

Today, FPGAs are being replaced with an “off-the-shelf” processor (Stretch S5000).

Software-configurations based on “clock rate”, such as the Stretch S5000 are an adaptive hybrid of the FPGA. Having software that is configurable within the processor associated with the general-purpose processor (GPPs) and DSPs and application specific processors (ASPs), serving parallelism and flexibility with FPGAs, programmable logic that is completely embedded inside the processor architecture.

Moreover, the Stretch S5000’s patented Instruction Set Extension Fabric (ISEF) is a game changer in the world of being able to program a processor for compute-intensive applications. The sky is the limit now for HFT to overcome and exploit exchange trade executions clock time.

ping bugs”

The “ping” comes from active sonar terminology so named by Mike Muuss in 1983. It is the means of sending a pulse to a target host across the Internet Protocol (IP) network. In consideration of market exchanges, the “ping” represents a “price prob” activated by an application programming interface (API) plugged into a specific market exchange.

Consequently, by using the “ping” proprietary data feeds (expensive subscription access) have a tremendous advantage over “public” (consumer) consolidated data feeds in consideration of trade execution latency. Even though The National Best Bid and Offer (NBBO) is meant to “halt” price dislocations (latency), but it has shown otherwise.

In light of the highly advanced computational algorithm trading systems such as value weighted average price (VWAP) and weighted average price (TWAP), HFT algorithms maintain an informational advantage by remaining constantly plugged into the major exchanges (listed below) to use latency issues to their advantage.

It is no longer the case that the price shown upon trade execution will be the fill price. Maintaining NBBO “best price” is undermined even more are inter-market sweep orders (ISO) and non-transparent dark pools that send a trade execution to multiple exchanges for instantaneous execution, disregarding the “best price” regulation. This is allowed by the SEC.

13 exchanges and nowhere to go”

Wall Street has two trading systems. Registered exchanges and alternative trading systems. The exchanges are regulated to provide the “best price” through the consolidated quotation system (CQS), and must file any rule changes with the Security and Exchange Commission(SEC).

The electronic communication networks (ECNs) and dark pools, do not provide CQS, but are mandated to match NBBO price quotations. In 2007, the Securities and Exchange Commission established Regulation National Market System (Reg NMS) to protect consumer traders from improprieties of the “best price” execution.

Reg NMS requires the exchanges to provide the quotes to the primary exchanges, such as NYSE. Data that is collected under the Security Information Processors (SIPs) for the NYSE and NASDAQ publish the National Best Bid and Offer (NBBO). Consequently, brokerage houses are required by Reg NMS to give consumer traders the best price at execution.

Out of the 13 exchanges accessed for market trading, the NASDAQ, NYSE, NYSE ARCA, BATS BZX, Direct Edge EDGX and EDGA have approximately eighty-eight percent of the lion’s share in total volumes. Dark pool trades, that are non-transparent account for more than 12% of the trading volume.


the larger the latency, the greater the uncertainty”

For consumer traders, this short duration of dislocation of price, becomes costly in commissions while bolstering optimal profits for HFTs. Empirical data comparison from examination of publicly traded market data and data sold directly from exchanges (tapped by High Frequency Trading algorithms) proves the fact that the “latency” of the consumer’s executed trade is picked off by HFTs, monitoring the data flow with direct access to the exchanges.

In one control study between the public NBBO and a synthetic NBBO (Redline Trading Source using a software programmed processor similar to the Stretch S5000) turned up 54,734 price dislocations; tabulated within 6.5 hours of the trading session with the equity Apple (AAPL).

It is estimated that price dislocations happened every 2.34 seconds with the latency lasting as long as 1.5 milliseconds. Consumer trades went to the wrong market exchange 0.175% of the time. The average price dislocation was $0.034.




The “packet-switched” network measured either “one-way” or “round trip” is being exploited as a “fixed game”.



As the world’s first cyber-security we were curious to investigate the PureFunds ISE Cyber Security ETF (NYSEARCA:HACK) that tracks the ISE Cyber Security Index (HXR).

Designed to deliver competitive returns, the overall asset classes of 30 securities included in the HACK ETF are approximately two-thirds software and programming and double digit allocation of communication equipment and mobile Internet devices.


Internationally, US based cyber-security firms lead at 72% over Israel (12%), Netherlands (5%), South Korea (5%), Japan (4%), Finland (2%), and Canada (1%) according to the Zack Funds report.

Clearly, publicly traded cyber-security firms that produce security solutions software against attacks on Internet of Things (IoT) devices are fast becoming highly sought after earners since the governments initiative to be proactive on legislation combating cyber-attacks.

Back in February 2014, bolstered by strong earnings and when President Obama pressed for new legislative initiatives to crack down IoT espionage,  the “cash on the barrel-head” stock CyberArk Software (NASDAQ:CYBR) skyrocketed.

CYBR was already showing an upward trajectory based on their quarterly net income at five times the previous fourth quarter in 2013 of $1.4 million.  Then it surged to a 52-week high of $72.48 in February before settling down to establish a new price strata in March around $50 per share.


The HACK’S three month performance on Market Value was 12.67%, rising to 15.54% this past month.  The top three holdings are Infoblox (NYSE:BLOX); CyberArk Software LTD (NASDAQ:CYBR) with 5.24% in total net assets, Fireeye, Inc. (NYSE:FEYE) with 5.19% and ProofPoint, Inc. (NYSE:PFPT) 5.16% in total net assets. As well, Palo Alto Networks, Inc (NASDAQ:PANW) and Qualys, Inc. (NASDAQ:QLYS).

Our volatility generator forecasts a 96.88% probability that HACK will hit $30.00 per share within the next 60 days.  Last Friday’s close was $27.84. Right now the price level is position near the 50% Fibonacci Ratio – showing a consolidation that precedes a breakout.

On March 26, HACK traded at an unusually high “buy” volume, a signal to us that its going into a 7-day Bullish trend.  This gives us confidence that an upward trend is in the making.  Listed below are all 30 assets in the HACK and their last “weights” performance (3/27/2015). Source: ISE Cyber Security Index.


Taking a lead from the projected increase in global security spending from $71.1 billion (2014) to $76.9 billion in 2015, three more cyber-security firms have announced that they are going public. Collectively, analysts are estimating a $1 billion or higher purchase total.  The firms are Rapid 7, LogRhythm and Veracode.


As deals flow to upgrade the cyber-security cycle in enterprising innovations coming on the market, coupled with the government’s “bullet train fast track” to take on the offensive against IoTs plaguing  American business and individuals, it is predicted that Wall Street traded cyber-security solutions sector’s profitability will be reach 25% or more by the end of this year.


Symbol Weights Company Name
PANW.N 4.69 Palo Alto Networks Inc.
SAIC.N 4.08 Science Applications International Corp
FTNT.OQ 4.65 Fortinet Inc
PFPT.OQ 4.82 Proofpoint Inc.
CUDA.N 3.96 Barracuda Networks Inc
RDWR.OQ 3.54 Radware Ltd
FEYE.OQ 5.17 FireEye Inc
SPLK.OQ 4.1 Splunk Inc.
QLYS.OQ 4.59 Qualys Inc.
BLOX.N 5.25 Infoblox Inc
IMPV.N 3.17 Imperva Inc
MANT.OQ 0.8 Mantech Intl Corp A
XLS.N 0.99 Exelis Inc.
SYMC.OQ 3.5 Symantec Corp
CHKP.OQ 4.06 Check Point Software (US)
CSCO.OQ 3.82 Cisco Systems Inc
ZIXI.OQ 0.77 Zix Corp.
FSC1V.H 2.55 F-Secure Oyj
JNPR.N 4 Juniper Networks Inc
CMP.WA 0.2 Comp SA
ABT.TO 0.78 Absolute Software Corp
GTO.AS 0.69 Gemalto NV
AVG.N 4.29 AVG Technologies NV
WYY.A 0.68 Widepoint Corp
IL.N 3.74 IntraLinks Holdings Inc
053800. 4.73 Ahnlab Inc
KEYW.OQ 3.17 Keyw Holding Corp
CYBR.OQ 5.2 Cyber-Ark Software Ltd/Israel
VDSI.OQ 3.16 VASCO Data Security Intl Inc
4704.T 4.26 Trend Micro Inc


The log-linear rule falls in between the “traders” price and the “net orders” affecting the price action.”  Prof. Doyne Farmer and Prof. Shareen Joshi*

Let’s be absolutely clear:  The National Best Bid and Offer (NBBO) is meant to protect the retail trader from pricing manipulation by their counter-party that could cheat them out of their profits, while benefiting the brokerage, proprietary dark pools and/or High Frequency Trading driven by their respective algorithms.

So I ask: Have you ever experience a “price dislocation”?  What I mean is that the price that you executed your exit at was blatantly offset so much – say over five cents – that an elephant could walk through it?  Well, you’re not alone.  Unless you the means of tracking this, say with an excel spreadsheet that is plugged into a brokerage house platform, you won’t know the origin of the “offset” that cut your calculated profits before closing.


Here is the comparison between the Thinkorswim (TOS) platform’s option chain for AAPL (Apple, Inc) premium prices and my Sharebuilder (SB) close price.  I traded AAPL at the APR option chain, the Strike price was 127.14.  My entry as shown below from the SB transaction history was a scaled in 2 contracts per 2 trades with a Long Call position.

My target limit was 2.05 on the Ask premium.  When 2.05 was hit I executed my close on the SB positions, but was you see, even though there was a drop in the premium on the TOS platform, the SB platform – connected to the BATS exchange – didn’t give me “best price” in accordance to NBBO rules.

sb aapl.jpeg (2)


Above is the SB transaction history.  My closing premium for all 4 contracts was 1.93, not anywhere near what the TOS platform was showing at the same Strike price.

2015-03-26-StockAndOptionQuoteForAAPL (2)


Just below the yellow highlighted ban is the current premium prices, last price and mark price, which all are well above the 1.93 closing price that SB gave me.  My profit loss was over $50 on the four contracts, leaving me with $16 in net profit.  Moreover, SB’s real-time price at this Strike price was previously held at 1.86 while the TOS platform’s Call premium price increased dramatically toward 2.05.  The lag time on the SB to catch up, and then not even matching “best price” as shown on the TOS platform didn’t exceed 1.96.


Whose the culprit behind this?  Conniving Leprechauns?  Pesky GPU malfunctions?  You may be surprised to learn that it boils down to High Frequency Trading algorithms (HFTs) trolling the exchanges for an opportunity to “flash trade” off of your executed trade; either when you open or close.  Since HFTs have direct access to contracted co-location to Wall Street exchanges, primarily located in New Jersey, their latency is measured in nanoseconds, whereas yours and mine are measured in milliseconds.


If you’re inspired to build an excel spreadsheet that will expose this detrimental price aberration you could turn to Walras’ formula:

dp over dt = -Beta D(p, …)

Or Kyle’s model formula:

P t+1 – P t = ω

But let’s keep it simple, as my point here is to just make you more aware of the fact that virtual pricing is overtaking your “true price” formation.  Take into consideration the first element in their formula concerning an asset or option premium’s price formation:


Form has two components that determine to be path dependent based on the price range (Bid/Offer) inputs provided by any one of the 13 market exchanges at any one second that eventually shows upon your computer screen.

The origin of the asset’s  “price” is fundamentally started at the opening of the market session and then sequential accumulation of both Ask and Bid share orders can be calibrated to determine intraday price trends.  That means if you set up an excel generator to record any equity Ask and Bid share orders, you can scale out a directional price movement forecast using the appropriate computational statistical mathematics.

According to Farmer & Joshi:

“a. This defines the weighted side which in turn shows the propensity toward formulating a trend that is either Bullish or Bearish.

b. Exponential Distribution equation defines the next calibration that is probability density accumulation.”

High Frequency Traders Can Shift “True Price”

There are 24,000 seconds during the Wall Street scramble to trade in one day session.  Within those 24,000 seconds, High Frequency Trading (machines talking to machines) causes 2.4 price dislocations, most often times cheating retail traders out of a few pennies on the equity’s Bid/Offer spread, including option’s premiums. That comes out to 57,600 price dislocations per trading day.


I have built a deterministic trading strategy that incorporates a quantitative excel spreadsheet “real-time” data input, calibrated to a set of parameters that eliminate the “noise” while showing the directional price formation of the underlying asset correlated to the options premium.  The most telling function is the price shifts and comparative profit between simulated Call/Put profits during intraday trading that are depicted on the GRTS Tactical Trader.

Below is a screenshot of the GRTS Tactical Trader spreadsheet:**

screenshot-{domain} {date} {time} (1)


I currently use TD Ameritrade, Thinkorswim, Dough, and Capital One Sharebuilder.  The reason is for the very reason I mentioned at the beginning of this article: tracking price dislocations, i.e. “flash trading” by HFTs that cause “virtual price dislocations” giving them a profitable edge on my trade executions, while I take a greater loss.


Rich K.

* “The dynamics of common trading strategies”, Farmer, Doyne, J. & Joshi, Shareen

** For TOS traders, the GRTS Tactical Trader is currently available in the Apache Open Source Excel format, for a token donation.  Inquiries via email are welcomed for further information and explanation.  This is for advanced users of excel and day traders.


Getting back on track with technical statistical analysis our summary Excel formulas assist in defining the optimal option premium/strike price to trade based on a number of values, set into our GRTS GENERATOR.  This is an all encompassing statistical data Excel spreadsheet that combines the underlying asset statistical analysis with their respective option chain.

We’ve calibrated a specific equation to signal an alert when a percentage pullback from the 52WK price high at a minimum of 12% with the optimal being 20%.  Second, the asset must show a higher than average liquidity characteristic for intraday trading.

On March 23rd TWITTER (TWTR) signaled an approximate 13% pull back from the previous high on February 26th of this year.

The 1HR Chart shows, compared to the Fibonacci Retracement, that TWTR bounced up from the 50% level, breaking through the 62% level, but there was not enough momentum in volume to keep it going north to the 78.6% level.  This is a fundamental move prior to a “breakout”.  Think of it like a sling-shot being pulled back before letting it go.  Typically, when you see a channel between the 50% and 62% Fibonacci levels that last over a week, there is a consolidation of inventory stacking up for a breakout.

This is where the DARVAS BOX (Devised by Nicholas Darvas who became a millionaire within 18 months by using this method) can validate your point of entry and exit.



The white rectangle box on the chart is the DARVAS BOX, starting with the high price point and down to the support (last price) for the closing day.

On Monday (March 23rd)  TWTR price went up, making a momentary breakthrough – $48.86 –  before fading back to $48.48 at the close.

Moment of truth was seen during extended hours – the light gray area on the chart – showing that the trend continued to favor the upside. Going into the opening today, TWTR confirmed our analysis that it was a Long Call buy.

Before the close, the price trend surpassed the +7.3%, closing at a a +8.21% overall move from Monday’s support price of $48.06, the best entry point that would have been covered on the intraday pull back before the close.

Taking a look at our GRTS Generator Excel spreadsheet, you can see our profit on the Front Month (APR), where we entered after it broke the “Previous Resistance” high price, shown on the 1HR chart.

Look for the “FRONT MONTH” to see our profit.

Stock quote and option quote for TWTR on 3/24/15 07:12:41
-56.31 -6.18 -1.16 1.94 0.7918
-0.34% -0.32% -0.04% 0.10% -0.08%
Mrkt Prfm Volatility Liquidity OTM Signal Last To Open
-0.150% -5.83% 0.20% Call Above
Asset Price 51.54 C-Return 1.0080
Net Change 3.080 Open-Last Inverse -0.0080
Price Action 4.310 2.87 Inverse P Act 0.0848
Bid 55.85 Net Ratio 50.8514 0.0283
Offer 51.46 0.715 0.4013 0.4869
Strategy Protective Put – April Long Put
Strike Entry Max Loss Stock Decline IV
50 1.22 2.26 47.74 0.3650
Front Month   Back Month
$70.55 -$62.00 $80.81 -$54.46
APR 15 (24) 100
03/24/15 05:17 PM
Call Front Month   Put Front Month
Premium 1.73 Premium 2.45
Entry Price 1.32 TWTR Entry Price 2.14
Intrinsic 1.65 Intrinsic 2.37
Premium TGT 1.98 Premium TGT 1.67
Delta Hedge 0.3792 Delta Hedge 0.3522
Gamma 0.0103 Call Spread Gamma 0.0246
Ask-Bid Spread 0.02 ~ Ask-Bid Spread 0.02
Prob Density 1.4489 Put Spread Prob Density 1.8033
Profit/Loss $70.55 ~ Profit/Loss -$62.00 

The “take-away” here is the validation of the move, and in this case TWTR came through, more so by breaking the 78.6% Fibonacci ceiling, closing today at $51.47.

The advantage of using this statistical analysis spreadsheet (plugged into the TOS platform) is its real-time data feed that gives you the opportunity to see which side of the option chain is being favored overall.  It may come early or it may take some time, but given our incorporation of the Covered-Call Return formula (shown in the GRTS Generator table as ‘C-Return’*, and Price Action indicator, we can have “leading indicators” that are based on computational mathematics – adaptive to the inputs and parameters calibrated to our own proprietary formulas.

You can have this GRTS Generator Excel Spreadsheet (Available in Apache Excel only), if you use TOS, for a token fee.  All equations and formulas are based on the conceptual approaches presented on Tastytrade by Tom Sosnoff and his team of experts and is meant to augment the Dough options trading platform as a means of seeing the reality of their formula constructs in real-time.

*C-Return:  This is a Covered-Call Return monetized formula.  If the the “Inverse” number is higher, than it’s a signal to lean into the Put side of the underlying asset.  This can change during intraday trading.

For more information regarding the GRTS Generator Excel Spreadsheet send me an email. If you’d like to request the GRTS Generator for a specific equity/asset you’re looking at trading, we’ll put it together for you, for a token payment.)

(Note: This presentation is for educational purposes only and not intended to predict or influence your own trading decisions.  The purpose is to show how technical analysis provides more in-depth insight versus the traditional indicators that are all based on historical data.  Using the Excel spreadsheet, we be more systematic by providing statistical simulations in the process of day trading.)


I’ve yet to hear anyone of the mainstream media market hacks say a thing about CYBR (Cyberark Software LTD ORD) that has shot up at over +66% or a Net Change of +$25 in the past ten days.

We did an entry on 2/10/2015 – preliminary to the White House’s Cybersecurity Order signed into legislation on 2/15/2015.

CYBR was an IPO last year.  We invested in it as one of the most promising up and coming equities to own in 2015 in our IPO equity portfolio.

As you can see on the chart, we invested in the FEB Option Chain – Long Call at the Strike price 35. The Bid premium was $.75 and Ask was $1.05 – a fairly wide spread.  Today, on the final day before FEB Expiration, we hit a $11,300 profit.



Considering all Hype formula kick-started by “The Interview” and Sony Pictures being hacked (a great clandestine story in and of itself) these are the kind of “fundamental” plays that one can calculate a strong probability of profit as this issue continued to be front page news, peaking with the White House move to start a more aggressive program on combating cyber-hacking warfare.


Many probably don’t recall that years ago Estonia was the victim of the first “country wide botnet assault” that completely shut down the country by the Russian Kremlin, when the state moved a 6-foot bronze statue memorial for the fallen Soviet Union Red Army soldier’s in WWII from Tallinn’s main square, out to the Russian soldier’s cemetery.  Not only did this result in riots in the capitol city’s streets, the demonstrators actions were a prelude to what was to come next:  The Kremlin’s all out assault on Estonia’s IT servers.

(Of the three Baltic States, Estonia is the least tolerant of Russian citizens living in their country.  Contrary to this prejudice, Lithuania gave Carte Blanche citizenship to all Russians working in their country when the Soviet Union collapsed.  Still, as former residence of the Baltics, I wouldn’t speak Russian outside of the capitol cities, as it would bring a wrath of knife stabbing stares and deliberate “cold shoulders”.)

As reported by WIRED: “Hackers Take Down The Most Wired Country in Europe”

“All major commercial banks, telcos, media outlets, and name servers — the phone books of the Internet — felt the impact, and this affected the majority of the Estonian population. This was the first time that a botnet threatened the national security of an entire nation.”




At the time, the only counterattack experts in this matter comprised of a handful of cybercops – called the Vetted.  A select few that could access the largest ISPs to “kick rogue computers off the network.”


If you want to bring down a country’s information infrastructure and you don’t want anyone to know who did it, the weapon of choice is a distributed denial of service attack. Using rented botnets, you can launch hundreds of thousands — even millions — of infobombs at a target, all while maintaining total deniability.  WIRED MAGAZINE: ISSUE 15.09

Today, CISCO (CSCO), Juniper (JNPR) and China’s Huawei networking devices et. al. are the high technology “cyber spies” for the front lines of burrowing their way into the security architecture of foreign countries, namely China and now North Korea.

(When I was working as an advisor in security surveillance for international cargo container shipping, I was told that certain US manufactured Internet servers sent to China’s universities, were rigged to send back their scientific research undetected.)

Read more: “U.S. to China: We Hacked Your Internet Gear We Told You Not To Hack


This is a “cut-to-the-chase” solution oriented task to find out if your chosen golden asset is volatile enough to make it a profitable option choice and what is its correlation to similar assets within its sector/classification?

Take the past history of the “asset” for the last 40 days (it’s metaphysical) from Google or Yahoo finance’s prices.

Paste into an excel spreadsheet workbook. Copy only the close price and paste into the second spreadsheet. Leave an empty cell above so you can put in the ticker symbol

Next to the price column, starting on the second cell below the first price, put in the Excel =stdev(First Price;Second Price) formula.

Fill out the remaining cells to obtain the standard deviations.

Take the “Line Graph” and use “Lines Only”.

Fill in the graph with the STDEV outcomes.

Here’s an example comparison between AAPL and IBM.


The blue line is AAPL and IBM is the orange line.  My take away is that IBM and AAPL would be a good selection for a portfolio.  Why?  They are diversified enough as you can see, they nearly move in opposite directions that translates into protecting your asset allocated profits.   IBM surprisingly to me is more volatile so there might be more option premium volatility versus AAPL.  This is something I’ll need to look into.

Meanwhile, keep the excel spreadsheet handy.  You can check just one asset to get a reality check on its percentage moves and volatility characteristics that will save you a lot of headache in tying up your occurrences with marginal volatility.







(Disclaimer:  This post is for educational purposes only.  I am not making any trading recommendations nor can held liable for one’s losses.  It is entirely up to you to decide what makes sense.  The take away here is a template formula that you can use for your own strategy building model.)

S&P 500,  DOW and NASDAQ are all bullish currently.  FOMC meeting minutes will be released at 2PM (EST).

Symbol Price Offer Net Chng P Act IV 15D SV SD P Target
TGT 76.56 76.81 2.59 0.2118 0.1455 0.50 1.26 79.682

Target (TGT) climbed during extended trading yesterday after the closing bell, only to skyrocket this morning breaking its previous 52 week high.  The trajectory peaked at $76.93 before the jet pack ran out of fuel.

We’re in a mid-day session pull back and flattening out at $76.61(-0.12%).

TGT started its Bull Run on November 11, 2014, after a long dry spell caught in a sojourning price range.   If you missed the November 18, 2014 entry point to capture the final leg up, then it’s pretty much a done deal for anymore excitement.

What could have carried TGT to a new high are two items:  The Christmas Ugly Sweater competitions and the announcement that Google (GOOG) partnered up with TGT on their latest “Art, Copy, & Code” interactive, in-store mobile experience designed to thrill Target consumers of all ages.

Context and Analysis

The  JAN 15 with 9 days left to expiration.  The IV (Implied Volatility) Rank is 65% and the HV (Historical Volatility) Rank is 45%. In our strategy rule book that’s a “SELL” signal.  Currently, the Price range standard deviation is 1.26, which in offsets the “SELL” signal because it’s higher than the HV.

The JAN 15 option chain Implied Volatility is 26.59%.  We can recalculate the Implied Volatility using a matrix equation that determines the “true” IV with a preset of percentages applied to specific days.  This formulary comes from the team at Tastytrade/Dough.

We’ll use the 0.577% (7 DAYS) to adjust the current IV: .2659 x 0.577 = .15%

This tells us that there is a 15% IV potential of premium movement up to the day of expiration.

On the Call side: There are +10K open interests at the 76 Strike with a net change of +1.06 gain on the premium.  The current Mark is 1.49, pulling back from a 1.55 high.

On the Put side: comparatively there’s not much open interest to be seen, except a +2K at the 75 Strike.  Net change is -1.07, comparatively to the Call net gain.

Contrarian Play

TGT historically doesn’t hold its new high price levels.  More of a range bound price formation trait, We’re going to watch TGT to wait for a “reduced cost basis” PUT premium price on the JAN 15 option chain at the 76 Strike price that is currently hovering around .95 with a day high of 1.04.

That means we’re watching for another price move upwards into an already overbought scenario ; the underlying target price is $75.50 – first red arrow – (34 Exponential Moving Average – EMA) to the breakout from the EMA consolidation – second red arrow – as shown on the chart below.  If TGT returns to the EMA consolidation breakout (that might become its new support price, we’ll have a 3% move on the premium.  One PUT contract will bring an estimated profit of $144.

Our strategic rule on this one is when the asset skyrockets in one day, they’ll be a 50% retracement back down from the highest high.  The hypothetical price target posted in the graph at top gives us an idea of the potential of price move still left in the underlying before entering our Long Put on the JAN 15 76 Strike.






Overwhelmingly, there are too many opportunities to short options this morning and or go Long on Puts.  Today’s volatility presents an opportunity to show one of our favorite plays for those not qualified for option spreads, yet can trade Covered Calls and Longs.

As mentioned in my previous post with the VXX, we trade it make up on drawdowns, or to exploit for day trade scalps.  Here is the strategic formulary. Overall, you can use the fundamental parameters of this strategy on any asset that has high Standard Deviation ratios I will be posting an example later).   AAPL is a prime example, and you’re probably enjoying a huge profit if you just went Long on the JAN 15 Puts this morning.



This is a viable trading strategy that is Risk Averse for the Day Trader.

Using the TOS platform, I put in the the following parameters on the Trade tab for options: Bid, Ask, Implied Volatility, Net Change, Mark and Last X with Strikes set at “8”.  This gives me the best “reduced cost basis” limit order entry point; though in such a market as today, I’m flying by the seat of my pants with discretionary executions.  My computer has overheated, just trying to keep with my Black Box calculations because of the massive amount of trading today. 


  • Expect a +4 to +5% move up – so you can use your Analysis Tab on TOS to see what the price target will be.  Once this is hit, I close out that position (Long Call, two legs up from the opening price.)
  • Target the highest Volume and Open Interest Strike Prices; correlative to the percentage move.
  • Use the Analysis Tab to determine the “price target” in relationship to the Premium’s earning potential
  • Watch the Last X price – relative to the Mark for the lowest, “best entry” point.
  • Execute
  • Pull back is about -1.5%.  On the chart I put the INTRADAY SUPPORT AT $32.80.  VXX retraced back to this point.
  • I moved up two more legs to the highest volume and open interest (provides greater volatility move on the premium; and entered a Long Call on the JAN 15 when there was a slight pull back in the Last X price that gave me a “reduced cost basis” entry – thus I was in “profit” when my limit order was executed.
  • I held this position for the final run up that is typically +1 to +2% or $33.57 and then closed.

However, the caveat, is that you don’t have access to our Option’s Black Box that provides a greater in-depth insight that exceeds Level II by a thousand miles in signal based trend to price formation.

This table snapshot below was posted at 12:30 (EST)

Ticker Current Offer % Change Net Change Price Action MoC NPAMC
VXX $33.56 33.56 5.10% 2.570 1.1300 0.13 11.0988
TLT $129.02 129.04 0.78% 1.700 0.5901 0.14 8.0903
AAPL $106.51 106.54 -1.67% -2.820 -1.2366 0.68 -2.3142

MoC – What is this?  The Measure of Certainty is a new formulary that is Lambda based on variance and co-variance price formation. The NPAMC is the ratio of the Net Change, Price Action and Measure of Certainty.  The higher the number the more robust it is in validation, comparable to the F-Test.   Notice that AAPL, which has made a dramatic drop today, has a NPAMC of -2.3142 and an MoC at .68.   Each trading instrument has a specific MoC numerical range, that can be translated into binary code for a signal based algorithm trading program.  The NPAMC is the “adaptive agent” in the algorithm.

With an hour and half left in the trading session, VXX is currently:

Ticker Current Offer % Change Net Change Price Action MoC NPAMC
VXX $33.31 33.36 4.38% 2.320 0.8800 0.09 15.8810

The MoC has decreased signaling a decrease in net share trading; the NPAMC shows us a “consolidation” of inventory.  If you were still in the VXX on a JAN 15 Long Call, you’d be kicking yourself for not getting out sooner.  (Having closed out VXX, one could have jumped the shark to AAPL entering on the JAN 15 Strike price of 107 for a +$1.70 premium move!)

Here’s the current chart of VXX that validates my Proof of Concept.  The support price at the 50% Fibonacci is being respected.  We’re sidelined until the “witching hour” when the market makers will start dumping inventory into the market that will cause a mean reversion price surge.  The current aggregate market performance is -1.84%, just below -2% which is the lowest overall percentage.  Only once have we seen a -4% drop during the day,


 Below is the VXX compared to the SPX on the 5MIN Chart.  They are nearly equal percentage moves, offset by 0.02%. If you wanted an entry point, the crossover would be your validation.



You have seen validation of our contextual “percentage move” strategy on trading Long Calls and Puts using the VXX as a day trade opportunity for profitable outcomes.  It’s not a perfect science, and one must intuit their own trade execution, but overall VXX has proven this pattern more than 80% of the time when market performance is -1% overall, with high sell off volatility.

Time to buy GOLD.



Disclaimer:  I’m not predicting or recommending you make these trades.  It is purely for educational purposes to provide you with a sharper image of how the market works so you develop your own strategic plan.


01/02/15 04:49 PM





Net Chng

P Act

IV 15D


























































































































































































About this graphic*:  At the very top of is the “Time Stamp”, then starting at the left we have the Number ID, Ticker Symbol, Close Price, Calibrated Price Offer, Net Change of the Day, Price Action of the Day, a calibrated Implied Volatility for a 15 day horizon, Statistical Volatility, Standard Deviation of the Price Range Set (Open, Current, Close, Day High/Low; Intraday Trend Directional Move, Boolean Logic (TRUE means current price is above the opening price of the day, FALSE means it’s below); the the price position percentage relative to the 52 WK High.  What more could you ask for in statistical, fuzzy logic analysis?

Context: What this shows as an aggregate picture is whether the asset is viable enough to trade  for a reasonable profit, proving insight to the directional move and price anomalies (PWRD).  We can compare pair correlations (FB and TWTR: Price Action is the leading indicator) and track “pull backs” during intraday trading (AAPL has a high Statistical Volatility).  We like to scalp VXX so here we see a disparity between the Net Change and Price Action that signals a change in direction along with the high Statistical Volatility meaning the price range is spread out.


1TSLA:  Bounced off the Fib 50% (202.48) for a text book pull back to the 38% (220.88) then headed south again.  On our graph – it’s a bearish trend at -24.74% below its 52 WK High.

2) HD: Since early August HD has been on a tear north.  Peaking with gains at +30.91%, we have a SELL signal now, as it dropped -2.44% from its 52WK High going into 2015.  Trading volume has been light, but we expect HD to head south with the current cold snap jet stream plaguing most of the Midwest.  HD is headed to 101.48 so lean into the Puts spreads for the final days of the JAN options.

3) UNG: With another Polar system blanketing much of the Midwest and Eastern seaboard in the US, UNG has dropped -37.6% since before November’s Thanksgiving day, over -408% for the year, and -46.36% from it’s yearly high, we think it’s hit bottom at $14.77 showing a glimmer of reality pricing.  Since 2008 UNG has dropped -485% below freezing; breaking its low of lows in 20911 ($15.74).  We don’t usually trade UNG, but it caught our eye today.  Going into the first quarter UNG typically is a bullish play.

4) LOW:  We threw it in just to compare to HD. Your call.

5) & 7)L TWTR & FB:  We expect a diversification of directional moves here.  TWTR is headed north and FB is headed south simply because one is overbought and one is oversold. Do the historical price comparison to the see the diversion. FB is right now squared off on the 62% Fib or $78.40 (Close was $78.48, but that splitting hairs).  We have a near perfect Triangle formation, that is split at the middle, meaning a new pivot price level.  But gravity is going to make its play on  FB so hang on to your hats as the market roller coasters is going to make a roller coaster drop on Monday’s opening.  FB will follow with at least a $2 buck loss (great – “break even” – Long Put set up for a short play on the JAN 15 options) to the 50% Fib or $77.35.  Make this a priority play in your game book, and signularly the best profit maker in the coming week along side AAPL and HD.

6) PWRD:  This is an example of a High Frequency Trade price dislocation that you’re not told about on CNBC.  Absolutely “front running” illegal “quote stuffing” ping driven nanosecond machine driven algorithms manipulating price setting.  If you didn’t know, HFTs now have algorithms that scan the market and geopolitical headlines for “high impact nouns, adjectives” that translated into designated binary coded syntax calibrated to the their trading algos that will trigger trade executions even before you’ve gotten the news on Twitter. Talk about having your finger on the “pulse” of everything.  Consequently, HFTs simply overwhelm the market makers at the opening and you just put a hundred million dollars in your offshore account.

8) AAPL: (or should it be Macintosh?): We could make a living just off of AAPL.  Gotta love it’s volatility and measure of uncertainty these days.  Our last trade, JAN 15 Long Put limit price entry was $113.04 on December 29, 2014 with a target price of $109.18.   In two days we gained 4.31% in price move on our JAN Long Put at the $113 Strike.

13)  VXX:  Our “player”.  It gained about 6% in the first half of trading, retreated, then bumped up as the S&P 500 dropped a smug +53% going into the close.   We’re in lots of welcomed volatility on this one so it’s staying on our radar for scalp option trades.  We use VXX to cover any drawdowns when the picking is ripe, and it usually is during some point in time during the trading session.

9, 10, 11, 14, 15):  FDX is going to remain bearish.  JNJ is undecided.  WFM is not a buy and hold asset.  Oh, wow, CNBC said WFM is up a whooping +817%… since 2008. That doesn’t tell me where its headed. The WFM, SFM and TFM: an exercise in correlative asset allocation.  TLT can be a robust player when the market has a a lot of bearish volatility, and a back up to VXX.  So we threw it in the basket.  YHOO is predictability transparent.

We put in a deep in the money Long Call with the JAN 15 option chain back in October, 2014. The peak price target of the underlying asset was $53.54 by the time NOV option expiration came around.  Ah, gee we were off by $.14 cents!  YHOO is caught in a sojourn range since hitting a support price of $48.85, this one has an earnings report coming out 11 days after the JAN 15 option expiration so expect some pickup in volatility  YHOO has been unusually quiet (low volumes) since Christmas Eve. YHOO exhibited a typical 7-day cyclic run north, then just fell like a rock, nearly going back to the previous low.  

When we see a stock struggling to tread higher price levels, it’s a signal that a bearish play is formulating.